DBMS > Atos Standard Common Repository vs. GreptimeDB vs. Kdb vs. Riak TS

System Properties Comparison Atos Standard Common Repository vs. GreptimeDB vs. Kdb vs. Riak TS

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

An open source Time Series DBMS built for increased scalability, high performance and efficiency

High performance Time Series DBMS

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Document store
Key-value store

Time Series DBMS

Time Series DBMS
Vector DBMS

Time Series DBMS

Secondary database models

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Score	7.73
Rank	#45	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

greptime.com

kx.com

Technical documentation

docs.greptime.com

code.kx.com

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Atos Convergence Creators

Greptime Inc.

Kx Systems, a division of First Derivatives plc

Open Source, formerly Basho Technologies

Initial release

2016

2022

2000

kdb was released 2000, kdb+ in 2003

2015

Current release

1703

3.6, May 2018

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free 32-bit version

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Rust

Erlang

Server operating systems

Linux

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

Linux
OS X

Data scheme

Schema and schema-less with LDAP views

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

table attribute 'grouped'

restricted

SQL

Support of SQL

yes

SQL-like query language (q)

yes, limited

APIs and other access methods

LDAP

gRPC
HTTP API
JDBC

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

HTTP API
Native Erlang Interface

Supported programming languages

All languages with LDAP bindings

C++
Erlang
Go
Java
JavaScript

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Python

user defined functions

Erlang

Triggers

yes

with views

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

LDAP bind authentication

Simple rights management via user accounts

rights management via user accounts

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
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provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
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tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
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Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
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kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

upon request
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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